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A comparison study between artificial neural network (ANN) and Genetic algorithms (GA) and Box-Jenkins (BJ) modeling in chaotic time series prediction

Habibeche. Mustapha, Benchikh. Tewfik, ELhendi. Hichem


Predicting the future behavior of chaotic time series in the last decade has become an important subject in statistical science. In this article, we are interested in the application of artificial neural networks and genetic algorithms to estimate the parameters of the chaos
time series simulated (Logistics Map Template), to confirm the effectiveness of these new mechanisms, as well as the method Box ; Jenkins then compare the results obtained.


Artificial Neural Networks, Genetic Algorithms; Time Series Chaotic Prediction; Method of Box and Jenkins.

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